I. Technical Field
The present invention relates generally to computer modeling and management of systems and, more particularly, to computer simulation techniques with real-time system monitoring and prediction of electrical system performance.
II. Background
Computer models of complex systems enable improved system design, development, and implementation through techniques for off-line simulation of the system operation. That is, system models can be created that computers can “operate” in a virtual environment to determine design parameters. All manner of systems can be modeled, designed, and virtually operated in this way, including machinery, factories, electrical power and distribution systems, processing plants, devices, chemical processes, biological systems, and the like. Such simulation techniques have resulted in reduced development costs and superior operation.
Design and production processes have benefited greatly from such computer simulation techniques, and such techniques are relatively well developed, but such techniques have not been applied in real-time, e.g., for real-time operational monitoring and management. In addition, predictive failure analysis techniques do not generally use real-time data that reflect actual system operation. Greater efforts at real-time operational monitoring and management would provide more accurate and timely suggestions for operational decisions, and such techniques applied to failure analysis would provide improved predictions of system problems before they occur. With such improved techniques, operational costs could be greatly reduced.
For example, mission critical electrical systems, e.g., for data centers or nuclear power facilities, must be designed to ensure that power is always available. Thus, the systems must be as failure proof as possible, and many layers of redundancy must be designed in to ensure that there is always a backup in case of a failure. It will be understood that such systems are highly complex, a complexity made even greater as a result of the required redundancy. Computer design and modeling programs allow for the design of such systems by allowing a designer to model the system and simulate its operation. Thus, the designer can ensure that the system will operate as intended before the facility is constructed.
Once the facility is constructed, however, the design is typically only referred to when there is a failure. In other words, once there is failure, the system design is used to trace the failure and take corrective action; however, because such design are complex, and there are many interdependencies, it can be extremely difficult and time consuming to track the failure and all its dependencies and then take corrective action that does not result in other system disturbances.
Moreover, changing or upgrading the system can similarly be time consuming and expensive, requiring an expert to model the potential change, e.g., using the design and modeling program. Unfortunately, system interdependencies can be difficult to simulate, making even minor changes risky.
Power Usage Effectiveness (PUE) and Data Center Infrastructure Efficiency (DCiE) are two very powerful analytic tools which enable data center operators to quickly estimate the energy efficiency of their data center, compare the results against other data centers, and determine if any energy efficiency improvements need to be made. However, PUE and DCiE are normally determined manually in an off-line mode. Consequently, a simulation model that allows data center operators to establish a base-line model of their data center and determine the PUE and DCiE using the model is desirable. Furthermore, a simulation model which utilizes an actual model of the facility to validate the base-line model is desirable.